A Novel Multisensory Stimulation and Data Capture System (MADCAP) for Investigating Sensory Trajectories in Infancy.

Sensory processing differences, including responses to auditory, visual, and tactile stimuli, are ideal targets for early detection of neurodevelopmental risks, such as autism spectrum disorder. However, most existing studies focus on the audiovisual paradigm and ignore the sense of touch. In this paper, we present a multisensory delivery system that can deliver audio, visual, and tactile stimuli in a controlled manner and capture peripheral physiological, eye gaze, and electroencephalographic response data. The novelty of the system is the ability to provide affective touch. In particular, we have developed a tactile stimulation device that delivers tactile stimuli to infants with precisely controlled brush stroking speed and force on the skin. A usability study of 10 3-20 month-old infants was conducted to investigate the tolerability and feasibility of the system. Results have shown that the system is well tolerated by infants and all the data were collected robustly. This paper paves the way for future studies charting the sensory response trajectories in infancy.

Design of an Autonomous Social Orienting Training System (ASOTS) for Young Children With Autism.

Social communication is among the core areas of impairment for children with Autism Spectrum Disorders (ASD). The training of social orientation is important for improving social communication of children with ASD. In recent years, technology-assisted ASD intervention had gained momentum due to its potential advantages in terms of precision, sustainability, flexibility and cost. In this paper, we propose a closed-loop autonomous computer system, named ASOTS, for training social orientation skills to young children with ASD. This system is designed to detect and track a child's attention in response to social orientation bids and help the child towards appropriate social orientation when needed. Response to name, an important social orientation skill, was used to demonstrate the functionality of the proposed system. Ten toddlers with ASD participated in a pilot user study to show whether the system could be used on young children who have been diagnosed with ASD. Another pilot user study with 10 TD infants tested whether this system has a potential to be applied for early detection for infants who were younger than the age when ASD diagnoses can be done. This was done intentionally to separately demonstrate utility and functionality for the clinical population of interest and to demonstrate functionality beyond current clinical identification capacity (i.e., infants). The results showed that the proposed system and the protocol were well tolerated by both groups, successfully captured young children's attention, and elicited the desired behavior.

Robot-Mediated Imitation Skill Training for Children With Autism.

Autism spectrum disorder (ASD) impacts 1 in 68 children in the U.S., with tremendous individual and societal costs. Technology-aided intervention, more specifically robotic intervention, has gained momentum in recent years due to the inherent affinity of many children with ASD towards technology. In this paper we present a novel robot-mediated intervention system for imitation skill learning, which is considered a core deficit area for children with ASD. The Robot-mediated Imitation Skill Training Architecture (RISTA) is designed in such a manner that it can operate either completely autonomously or in coordination with a human therapist depending on the intervention need. Experimental results are presented from small user studies validating system functionality, assessing user tolerance, and documenting subject performance. Preliminary results show that this novel robotic system draws more attention from the children with ASD and teaches gestures more effectively as compared to a human therapist. While no broad generalized conclusions can be made about the effectiveness of RISTA based on our small user studies, initial results are encouraging and justify further exploration in the future.

A step towards developing adaptive robot-mediated intervention architecture (ARIA) for children with autism.

Emerging technology, especially robotic technology, has been shown to be appealing to children with autism spectrum disorders (ASD). Such interest may be leveraged to provide repeatable, accurate and individualized intervention services to young children with ASD based on quantitative metrics. However, existing robot-mediated systems tend to have limited adaptive capability that may impact individualization. Our current work seeks to bridge this gap by developing an adaptive and individualized robot-mediated technology for children with ASD. The system is composed of a humanoid robot with its vision augmented by a network of cameras for real-time head tracking using a distributed architecture. Based on the cues from the child's head movement, the robot intelligently adapts itself in an individualized manner to generate prompts and reinforcements with potential to promote skills in the ASD core deficit area of early social orienting. The system was validated for feasibility, accuracy, and performance. Results from a pilot usability study involving six children with ASD and a control group of six typically developing (TD) children are presented.